Top Remote Analysis Reporting Jobs in San Diego, CA

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Founding data engineer to design and build Payabli's data platform: architect lakehouse/warehouse, build batch and streaming pipelines, model canonical datasets, ensure data quality/observability, enforce access/masking/lineage for regulated financial data, and enable analytics/ML feature pipelines while establishing team standards and CI/CD.

The Product Analyst will analyze product performance, develop reports, and collaborate with stakeholders to enhance pet insurance offerings through data-driven insights.

Drive Data Governance requirements, analyze and validate data, collaborate with stakeholders, and maintain Data Governance artifacts using SQL and Informatica tools.

The Analytics Architect will design and implement cloud-based analytics solutions, maintain data pipelines, ensure data quality, and collaborate with teams to enhance operational efficiency.

The Data and Reporting Architect will lead the design of data architectures and reporting systems, addressing complex data challenges and ensuring compliance with regulatory standards. Responsibilities include mentoring engineers, defining data quality frameworks, and collaborating with various teams to implement scalable solutions.

Design, develop, and optimize Tableau dashboards and data sources on Redshift; collaborate with data engineering (dbt) and business teams; own Tableau governance, performance tuning, documentation, training, and ensure data security compliance.

The Senior Data Analyst transforms data into insights to guide business decisions, conducts analyses, and improves data collection systems.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

Lead customer-facing data engineering and warehousing initiatives on the Databricks platform. Architect and optimize production-scale ETL/ELT pipelines, performance-test workloads, migrate legacy systems to cloud lakehouse architectures, support Solution Architects in technical sales, and provide training, demos, and community contributions.